<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v2.0 20040830//EN" "journalpublishing.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="2.0" xml:lang="en" article-type="research-article"><front><journal-meta><journal-id journal-id-type="nlm-ta">JMIR Form Res</journal-id><journal-id journal-id-type="publisher-id">formative</journal-id><journal-id journal-id-type="index">27</journal-id><journal-title>JMIR Formative Research</journal-title><abbrev-journal-title>JMIR Form Res</abbrev-journal-title><issn pub-type="epub">2561-326X</issn><publisher><publisher-name>JMIR Publications</publisher-name><publisher-loc>Toronto, Canada</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">v10i1e96940</article-id><article-id pub-id-type="doi">10.2196/96940</article-id><article-categories><subj-group subj-group-type="heading"><subject>Original Paper</subject></subj-group></article-categories><title-group><article-title>Changes in Microbial Foodborne Pathogen Detection in Beijing, China, Before and After the COVID-19 Pandemic: Single-Center Retrospective Study</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes" equal-contrib="yes"><name name-style="western"><surname>Liang</surname><given-names>Chao</given-names></name><degrees>BSc</degrees><xref ref-type="aff" rid="aff1"/><xref ref-type="fn" rid="equal-contrib1">*</xref></contrib><contrib contrib-type="author" equal-contrib="yes"><name name-style="western"><surname>Tan</surname><given-names>Luping</given-names></name><degrees>BSc</degrees><xref ref-type="aff" rid="aff1"/><xref ref-type="fn" rid="equal-contrib1">*</xref></contrib><contrib contrib-type="author"><name name-style="western"><surname>Zhang</surname><given-names>Hongyi</given-names></name><degrees>BSc</degrees><xref ref-type="aff" rid="aff1"/></contrib></contrib-group><aff id="aff1"><institution>Department of Infectious Diseases, Peking University Third Hospital</institution><addr-line>No. 49, Huayuan North Road, Haidian District</addr-line><addr-line>Beijing</addr-line><country>China</country></aff><contrib-group><contrib contrib-type="editor"><name name-style="western"><surname>Steenstra</surname><given-names>Ivan</given-names></name></contrib></contrib-group><contrib-group><contrib contrib-type="reviewer"><name name-style="western"><surname>Meddeb</surname><given-names>Khaoula</given-names></name></contrib><contrib contrib-type="reviewer"><name name-style="western"><surname>Baharom</surname><given-names>Nizam</given-names></name></contrib></contrib-group><author-notes><corresp>Correspondence to Chao Liang, BSc, Department of Infectious Diseases, Peking University Third Hospital, No. 49, Huayuan North Road, Haidian District, Beijing, 100191, China, 86 15210753436; <email>liang1chao1@126.com</email></corresp><fn fn-type="equal" id="equal-contrib1"><label>*</label><p>these authors contributed equally</p></fn></author-notes><pub-date pub-type="collection"><year>2026</year></pub-date><pub-date pub-type="epub"><day>21</day><month>9</month><year>2026</year></pub-date><volume>10</volume><elocation-id>e96940</elocation-id><history><date date-type="received"><day>02</day><month>04</month><year>2026</year></date><date date-type="rev-recd"><day>01</day><month>09</month><year>2026</year></date><date date-type="accepted"><day>01</day><month>09</month><year>2026</year></date></history><copyright-statement>&#x00A9; Chao Liang, Luping Tan, Hongyi Zhang. Originally published in JMIR Formative Research (<ext-link ext-link-type="uri" xlink:href="https://formative.jmir.org">https://formative.jmir.org</ext-link>), 21.9.2026. </copyright-statement><copyright-year>2026</copyright-year><license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/"><p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (<ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link>), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on <ext-link ext-link-type="uri" xlink:href="https://formative.jmir.org">https://formative.jmir.org</ext-link>, as well as this copyright and license information must be included.</p></license><self-uri xlink:type="simple" xlink:href="https://formative.jmir.org/2026/1/e96940"/><abstract><sec><title>Background</title><p>Foodborne diseases remain a significant global public health concern, imposing substantial health and economic burdens. The COVID-19 pandemic altered health care&#x2013;seeking behaviors, infection control practices, and infectious disease epidemiology; however, its association with microbial foodborne pathogens remains incompletely characterized.</p></sec><sec><title>Objective</title><p>This single-center retrospective study aimed to analyze changes in bacterial and viral foodborne pathogen detection using clinical and etiological data from patients at an infectious diarrhea clinic in a tertiary Beijing hospital over 6 years and to inform prevention strategies in the postpandemic era.</p></sec><sec sec-type="methods"><title>Methods</title><p>We collected data from patients presenting to the Infectious Diarrhea Clinic of Peking University Third Hospital (a grade A tertiary care center serving the Haidian District and surrounding areas of Beijing) from January 2018 to December 2019 (prepandemic) and from January 2022 to December 2023 (postpandemic). The years 2020 and 2021 were excluded due to major disruptions in clinical services and surveillance during the peak pandemic period. Etiological results were obtained from the Beijing Haidian District Center for Disease Control and Prevention. Diagnostic methods, laboratory protocols, specimen collection procedures, reagent kits, instrumentation, and testing criteria remained consistent throughout the study period. Cases were divided into 2 groups based on time period, and <italic>&#x03C7;</italic>2 tests were used for comparisons. The positivity rate was calculated as patients with at least 1 target pathogen detected divided by all patients who provided stool specimens.</p></sec><sec sec-type="results"><title>Results</title><p>In total, 1064 patients were included (561 in group A and 503 in group B). From 2018 to 2019, 155/561 specimens tested positive for foodborne pathogens (27.6%, 95% CI 23.9%&#x2010;31.3%), including 22 <italic>Salmonella</italic>, 24 <italic>Vibrio parahaemolyticus</italic>, 66 diarrheagenic <italic>Escherichia coli</italic> (DEC), and 43 <italic>Norovirus</italic> cases. From 2022 to 2023, 82/503 specimens tested positive (16.3%, 95% CI 13.1%&#x2010;19.5%), including 13 <italic>Salmonella</italic>, 7 <italic>V parahaemolyticus</italic>, 45 DEC, and 17 <italic>Norovirus</italic> cases. The overall positivity rate was significantly lower in the postpandemic period than in the prepandemic period (27.6% vs 16.3%, <italic>P</italic>&#x003C;.05). Students and males aged 16&#x2010;25 years were the most represented demographic groups. DEC remained the predominant pathogen in both periods. The detection rates of <italic>V parahaemolyticus</italic>, from 24/561 (4.3%) to 7/503 (1.4%) (<italic>P</italic>=.005), and <italic>Norovirus</italic>, from 43/561 (7.7%) to 17/503 (3.4%) (<italic>P</italic>=.002), were significantly lower in the postpandemic period.</p></sec><sec sec-type="conclusions"><title>Conclusions</title><p>Among patients attending a single infectious diarrhea clinic in Beijing, the detection rates of microbial foodborne pathogens were significantly lower in the postpandemic period compared with the prepandemic period. These findings may reflect changes in health care&#x2013;seeking behavior, infection control practices, food consumption patterns, and/or testing practices during this period; however, this observational study cannot establish causation. Targeted surveillance and health education for students and young adults remain important. These results may not be generalizable to community-level incidence or other settings; further multicenter studies are warranted.</p></sec></abstract><kwd-group><kwd>descriptive analysis</kwd><kwd>etiology</kwd><kwd>epidemiology</kwd><kwd>microbial foodborne pathogens</kwd><kwd>diarrheagenic Escherichia coli</kwd><kwd>COVID-19 pandemic</kwd><kwd>single-center study</kwd></kwd-group></article-meta></front><body><sec id="s1" sec-type="intro"><title>Introduction</title><p>Foodborne diseases comprise a category of infectious or toxic conditions caused by various pathogenic factors that enter the human body through food intake [<xref ref-type="bibr" rid="ref1">1</xref>]. These diseases not only cause physical harm but also affect the development of national food safety industries and impose substantial economic burdens, both of which are receiving increasing attention. Since 2010, China has established a national foodborne disease reporting system and an outbreak reporting system [<xref ref-type="bibr" rid="ref2">2</xref>]. According to the World Health Organization, approximately one-tenth of the global population suffers from foodborne microbial infections annually, placing a heavy burden on public health [<xref ref-type="bibr" rid="ref3">3</xref>]. Over the past decade, China has recorded over 30,000 foodborne disease outbreaks involving nearly 260,000 cases, and an estimated 200 million people are affected each year [<xref ref-type="bibr" rid="ref4">4</xref>].</p><p>Foodborne diseases have become a key focus in China. Since 2020, the novel coronavirus has continued to spread and evolve across more than 200 countries and regions. During the COVID-19 pandemic, increases in respiratory syncytial virus infections in Canada [<xref ref-type="bibr" rid="ref5">5</xref>], influenza infections [<xref ref-type="bibr" rid="ref6">6</xref>], and bloodstream infections in Europe and the United States [<xref ref-type="bibr" rid="ref7">7</xref>,<xref ref-type="bibr" rid="ref8">8</xref>] have been reported. Studies have also described significant changes in bacterial colonization patterns during the pandemic, which may pose potential public health risks [<xref ref-type="bibr" rid="ref9">9</xref>]. In addition, bacterial infections caused by <italic>Streptococcus pneumoniae</italic>, <italic>Haemophilus influenzae</italic>, and <italic>Mycoplasma pneumoniae</italic> have increased following the pandemic [<xref ref-type="bibr" rid="ref10">10</xref>].</p><p>Assessing the association between the COVID-19 pandemic and other infectious diseases is crucial for infection prevention and control. Several studies have documented changes in gastrointestinal infections during the pandemic, with many reporting reductions in enteric pathogen detection coinciding with nonpharmaceutical interventions, such as hand hygiene, mask wearing, and social distancing. However, most existing studies have focused on Western populations, and data from hospital-based settings in China remain limited, particularly regarding the postpandemic period of 2022&#x2010;2023. This single-center retrospective study aimed to analyze changes in the detection patterns of bacterial and viral foodborne pathogens by conducting an in-depth analysis of clinical and etiological data from patients attending an infectious diarrhea clinic at a tertiary hospital in Beijing over a 6-year period and to provide evidence to inform prevention strategies in the postpandemic era.</p></sec><sec id="s2" sec-type="methods"><title>Methods</title><sec id="s2-1"><title>Study Setting and Data Collection</title><p>This retrospective study was conducted at the Infectious Diarrhea Clinic of Peking University Third Hospital, a large grade A tertiary care hospital located in Haidian District, Beijing. The clinic serves a diverse population, including local residents, university students from surrounding academic institutions, and referred patients from the community. It functions as a primary and a secondary care access point, as well as a tertiary referral center. Data were collected from patients treated for foodborne diseases during two periods: January 2018 to December 2019 (group A, prepandemic) and January 2022 to December 2023 (group B, postpandemic).</p><p>The years 2020 and 2021 were excluded from the analysis because they represent the peak of the COVID-19 pandemic in Beijing, during which routine infectious diarrhea clinic services were substantially disrupted, surveillance protocols were altered, and patient care-seeking patterns were profoundly affected. We acknowledge that excluding this period creates a discontinuity in the temporal trends and limits our ability to capture changes during the most intense phase of the pandemic; however, data from this interval were considered unreliable for comparative analysis because of these major disruptions.</p></sec><sec id="s2-2"><title>Inclusion Criteria</title><p>Inclusion criteria were patients aged 16 years or older presenting to the Infectious Diarrhea Clinic and having illness onset associated with food intake or suspected food intake, accompanied by gastrointestinal symptoms, including nausea, vomiting, abdominal pain, and diarrhea.</p><p>Exclusion criteria were patients with gastrointestinal diseases clearly diagnosed as nonfoodborne. This study focused exclusively on bacterial and viral foodborne pathogens; nonmicrobial foodborne illnesses, such as those caused by chemical contamination, naturally occurring toxins, or food allergies, were not included in the etiological testing panel and therefore are not represented in these results.</p></sec><sec id="s2-3"><title>Laboratory Methods</title><p>For patients visiting the Infectious Diarrhea Clinic, demographic information (name, age, occupation), clinical symptoms (abdominal pain, diarrhea, fever, fatigue), suspected food exposure history, and stool specimens were collected. Specimens were sent weekly to the Haidian District Center for Disease Control and Prevention for testing, with results reviewed by the Beijing Center for Disease Control and Prevention. Importantly, the diagnostic methods, laboratory protocols, specimen collection procedures, reagent kits, instrumentation, and testing criteria remained unchanged throughout the study period (2018&#x2010;2023), with no modifications made to the pathogen testing panel or definitions of positive results.</p><p>Laboratory analyses followed the <italic>National Foodborne Pathogen Monitoring Manual</italic> for isolation, culture, and identification (2015&#x2010;2019). Initial screening involved streaking specimens onto agar plates with 24-hour incubation. For positive screens, 5 suspicious diarrheagenic <italic>Escherichia coli</italic> (DEC) colonies were selected and subjected to biochemical identification using a VITEK2 Compact30 automated system (bioM&#x00E9;rieux Inc).</p><p>The 5 target pathogens monitored were <italic>Salmonella</italic>, <italic>Shigella</italic>, <italic>Vibrio parahaemolyticus</italic>, DEC, and <italic>Norovirus</italic>. A specimen was considered etiologically positive if at least 1 of these 5 pathogens was detected. The positivity rate was calculated as the number of positive specimens divided by the total number of patients whose stool specimens were collected and submitted for testing.</p></sec><sec id="s2-4"><title>Ethical Considerations</title><p>This study was approved by the Medical Scientific Research Ethics Committee of Peking University Third Hospital (2024 Medical Ethics Review number 203&#x2010;01). All study participants provided informed consent. The study was conducted in accordance with the Declaration of Helsinki.</p></sec><sec id="s2-5"><title>Statistical Analysis</title><p>Data were organized and summarized using Microsoft Excel. Statistical analyses were performed using SPSS version 26.0 for Mac (SPSS Inc). Cases were divided into 2 groups: group A (2018&#x2010;2019) and group B (2022&#x2010;2023). Age was compared between groups using independent-samples <italic>t</italic> tests. Qualitative data were expressed as numbers (percentages), and 95% CIs were calculated for key proportions. Group comparisons were made using <italic>&#x03C7;</italic><sup>2</sup> tests, with <italic>P</italic>&#x003C;.05 considered statistically significant.</p></sec></sec><sec id="s3" sec-type="results"><title>Results</title><sec id="s3-1"><title>General Information</title><p>From January 2018 to December 2019 and from January 2022 to December 2023, a total of 1064 cases meeting the inclusion criteria were seen at the Infectious Diarrhea Clinic. Among them, 561 (52.7%) were male and 503 (47.3%) were female. The predominant age group was 26 to 45 years (n=479, 45%). The top 3 occupations were students (n=377, 35.4%), civil servants (n=284, 26.7%), and retired personnel (n=101, 9.5%). <xref ref-type="table" rid="table1">Table 1</xref> presents a comparison of the demographic and occupational characteristics of groups A and B. Clinical symptoms among the cases are summarized in <xref ref-type="table" rid="table2">Table 2</xref>. The digestive system was the most commonly affected system in both groups (group A: 554/561, 98.8%; group B: 496/503, 98.6%). General symptoms were significantly more frequent in the prepandemic group (group A: 176/561, 31.4%; group B: 62/503, 12.3%; P&#x003C;.001), while respiratory, cardiovascular/cerebrovascular, urinary, and nervous system symptoms were rare in both groups.</p><table-wrap id="t1" position="float"><label>Table 1.</label><caption><p>Demographic and occupational characteristics of the study population (N=1064).</p></caption><table id="table1" frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom">Characteristic</td><td align="left" valign="bottom">Overall (N=1064), n (%)</td><td align="left" valign="bottom">Group A (N=561), n (%)</td><td align="left" valign="bottom">Group B (N=503), n (%)</td></tr></thead><tbody><tr><td align="left" valign="top" colspan="4">Gender</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Male</td><td align="left" valign="top">561 (52.7)</td><td align="left" valign="top">295 (52.6)</td><td align="left" valign="top">266 (52.9)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Female</td><td align="left" valign="top">503 (47.3)</td><td align="left" valign="top">266 (47.4)</td><td align="left" valign="top">237 (47.1)</td></tr><tr><td align="left" valign="top" colspan="4">Age group</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>16&#x2010;25 years</td><td align="left" valign="top">411 (38.6)</td><td align="left" valign="top">198 (35.3)</td><td align="left" valign="top">213 (42.3)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>26&#x2010;45 years</td><td align="left" valign="top">479 (45)</td><td align="left" valign="top">274 (48.8)</td><td align="left" valign="top">205 (40.8)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>46&#x2010;65 years</td><td align="left" valign="top">118 (11.1)</td><td align="left" valign="top">64 (11.4)</td><td align="left" valign="top">54 (10.7)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>&#x003E;65 years</td><td align="left" valign="top">56 (5.3)</td><td align="left" valign="top">25 (4.5)</td><td align="left" valign="top">31 (6.2)</td></tr><tr><td align="left" valign="top" colspan="4">Occupation</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Student</td><td align="left" valign="top">377 (35.4)</td><td align="left" valign="top">180 (32.1)</td><td align="left" valign="top">197 (39.2)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Civil servant</td><td align="left" valign="top">284 (26.7)</td><td align="left" valign="top">167 (29.8)</td><td align="left" valign="top">117 (23.3)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Retired</td><td align="left" valign="top">101 (9.5)</td><td align="left" valign="top">47 (8.4)</td><td align="left" valign="top">54 (10.7)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Homemaker/unemployed</td><td align="left" valign="top">35 (3.3)</td><td align="left" valign="top">28 (5)</td><td align="left" valign="top">7 (1.4)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Worker/migrant worker</td><td align="left" valign="top">19 (1.8)</td><td align="left" valign="top">16 (2.9)</td><td align="left" valign="top">3 (0.6)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Teacher</td><td align="left" valign="top">16 (1.5)</td><td align="left" valign="top">9 (1.6)</td><td align="left" valign="top">7 (1.4)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Food service</td><td align="left" valign="top">7 (0.7)</td><td align="left" valign="top">6 (1.1)</td><td align="left" valign="top">1 (0.2)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Medical staff</td><td align="left" valign="top">11 (1)</td><td align="left" valign="top">9 (1.6)</td><td align="left" valign="top">2 (0.4)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Farmer/fisherman</td><td align="left" valign="top">3 (0.3)</td><td align="left" valign="top">2 (0.4)</td><td align="left" valign="top">1 (0.2)</td></tr><tr><td align="left" valign="top"><named-content content-type="indent">&#x00A0;&#x00A0;&#x00A0;&#x00A0;</named-content>Other/unknown</td><td align="left" valign="top">211 (19.8)</td><td align="left" valign="top">97 (17.3)</td><td align="left" valign="top">114 (22.7)</td></tr></tbody></table></table-wrap><table-wrap id="t2" position="float"><label>Table 2.</label><caption><p>Distribution of clinical symptoms among cases.</p></caption><table id="table2" frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom">Symptom system</td><td align="left" valign="bottom">Group A (N=561), n (%)</td><td align="left" valign="bottom">Group B (N=503), n (%)</td></tr></thead><tbody><tr><td align="left" valign="top">Digestive system</td><td align="left" valign="top">554 (98.8)</td><td align="left" valign="top">496 (98.6)</td></tr><tr><td align="left" valign="top">General symptoms</td><td align="left" valign="top">176 (31.4)</td><td align="left" valign="top">62 (12.3)</td></tr><tr><td align="left" valign="top">Respiratory system</td><td align="left" valign="top">2 (0.4)</td><td align="left" valign="top">0 (0)</td></tr><tr><td align="left" valign="top">Cardiovascular/cerebrovascular</td><td align="left" valign="top">2 (0.4)</td><td align="left" valign="top">0 (0)</td></tr><tr><td align="left" valign="top">Urinary system</td><td align="left" valign="top">1 (0.2)</td><td align="left" valign="top">0 (0)</td></tr><tr><td align="left" valign="top">Nervous system</td><td align="left" valign="top">5 (0.9)</td><td align="left" valign="top">3 (0.6)</td></tr></tbody></table></table-wrap></sec><sec id="s3-2"><title>History of Suspected Food Exposure</title><p><xref ref-type="table" rid="table3">Table 3</xref> shows that mixed foods accounted for the highest proportion in both groups, followed by meat and meat products. <italic>&#x03C7;</italic><sup>2</sup> tests revealed statistically significant differences between the 2 groups in the proportions of cases associated with vegetables and their products, grains and their products, and other foods (<italic>P</italic>&#x003C;.05). The number of cases related to vegetables and their products decreased from 79 to 41 in the postpandemic period, while cases related to grains and their products increased from 24 to 47, and those related to other foods increased from 56 to 70.</p><table-wrap id="t3" position="float"><label>Table 3.</label><caption><p>Suspected food exposure history among foodborne disease cases.</p></caption><table id="table3" frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom">Food category</td><td align="left" valign="bottom">Overall (N=1064), n (%)</td><td align="left" valign="bottom">Group A (N=561), n (%)</td><td align="left" valign="bottom">Group B (N=503), n (%)</td><td align="left" valign="bottom">Chi-square (<italic>df</italic>)</td><td align="left" valign="bottom"><italic>P</italic> value</td></tr></thead><tbody><tr><td align="left" valign="top">Meat and products</td><td align="left" valign="top">217 (20.4)</td><td align="left" valign="top">125 (22.3)</td><td align="left" valign="top">92 (18.3)</td><td align="left" valign="top">2.6&#xFF08;1&#xFF09;</td><td align="left" valign="top">.11</td></tr><tr><td align="left" valign="top">Vegetables and products</td><td align="left" valign="top">120 (11.3)</td><td align="left" valign="top">79 (14.1)</td><td align="left" valign="top">41 (8.2)</td><td align="left" valign="top">9.3&#xFF08;1&#xFF09;</td><td align="left" valign="top">.002</td></tr><tr><td align="left" valign="top">Mixed foods</td><td align="left" valign="top">378 (35.5)</td><td align="left" valign="top">196 (34.9)</td><td align="left" valign="top">182 (36.2)</td><td align="left" valign="top">0.2&#xFF08;1&#xFF09;</td><td align="left" valign="top">.67</td></tr><tr><td align="left" valign="top">Fruits and products</td><td align="left" valign="top">78 (7.3)</td><td align="left" valign="top">36 (6.4)</td><td align="left" valign="top">42 (8.4)</td><td align="left" valign="top">1.5&#xFF08;1&#xFF09;</td><td align="left" valign="top">.23</td></tr><tr><td align="left" valign="top">Grains and products</td><td align="left" valign="top">71 (6.7)</td><td align="left" valign="top">24 (4.3)</td><td align="left" valign="top">47 (9.3)</td><td align="left" valign="top">10.9&#xFF08;1&#xFF09;</td><td align="left" valign="top">&#x003C;.001</td></tr><tr><td align="left" valign="top">Aquatic products</td><td align="left" valign="top">74 (7)</td><td align="left" valign="top">45 (8)</td><td align="left" valign="top">29 (5.8)</td><td align="left" valign="top">2.1&#xFF08;1&#xFF09;</td><td align="left" valign="top">.15</td></tr><tr><td align="left" valign="top">Other Foods</td><td align="left" valign="top">126 (11.8)</td><td align="left" valign="top">56 (10)</td><td align="left" valign="top">70 (13.9)</td><td align="left" valign="top">3.9&#xFF08;1&#xFF09;</td><td align="left" valign="top">.047</td></tr></tbody></table></table-wrap></sec><sec id="s3-3"><title>Etiological Results</title><p><xref ref-type="fig" rid="figure1">Figure 1</xref> compares the number of positive cases for each of the 5 monitored pathogens between the 2 periods. The overall pathogen positivity rate among all tested patients was 22.3% (237/1064). Group A had a positivity rate of 27.6% (155/561, 95% CI 23.9%&#x2010;31.3%), which was significantly higher than the 16.3% (82/503, 95% CI 13.1%&#x2010;19.5%) observed in group B (<italic>P</italic>&#x003C;.05). Annual surveillance data showed the following results: 2018 (228 tested, 65 positive), 2019 (333 tested, 90 positive), 2022 (259 tested, 24 positive), and 2023 (244 tested, 58 positive).</p><fig position="float" id="figure1"><label>Figure 1.</label><caption><p>Comparison of etiological results between group A and group B of foodborne diseases.</p></caption><graphic alt-version="no" mimetype="image" position="float" xlink:type="simple" xlink:href="formative_v10i1e96940_fig01.png"/></fig><p>Five pathogens were monitored: <italic>Salmonella</italic>, <italic>Shigella</italic>, <italic>V parahaemolyticus</italic>, DEC, and <italic>Norovirus</italic>. No <italic>Shigella</italic> cases were detected in either group. The detection rate of <italic>V parahaemolyticus</italic> among all tested patients was significantly lower in group B (7/503, 1.4%) than in group A (24/561, 4.3%) (<italic>P</italic>=.005). No statistically significant differences were observed for <italic>Salmonella</italic> (group A: 22/561, 3.9%; group B: 13/503, 2.6%) or DEC (group A: 66/561, 11.8%; group B: 45/503, 9%). The detection rate of <italic>Norovirus</italic> was significantly lower in group B (17/503, 3.4%) than in group A (43/561, 7.7%) (<italic>P</italic>=.002) (<xref ref-type="table" rid="table4">Table 4</xref>).</p><table-wrap id="t4" position="float"><label>Table 4.</label><caption><p>Comparison of etiological results between group A and group B.</p></caption><table id="table4" frame="hsides" rules="groups"><thead><tr><td align="left" valign="bottom">Item</td><td align="left" valign="bottom">Cases (N=1064), n</td><td align="left" valign="bottom">Proportion (%)</td><td align="left" valign="bottom">Group A (N=561), n (%)</td><td align="left" valign="bottom">Group B (N=503), n (%)</td><td align="left" valign="bottom">Chi-square (<italic>df</italic>)</td><td align="left" valign="bottom"><italic>P</italic> value</td></tr></thead><tbody><tr><td align="left" valign="top">Positive cases<sup><xref ref-type="table-fn" rid="table4fn1">a</xref></sup></td><td align="left" valign="top">237</td><td align="left" valign="top">22.3</td><td align="left" valign="top">155 (27.6)</td><td align="left" valign="top">82 (16.3)</td><td align="left" valign="top">19.7&#xFF08;1&#xFF09;</td><td align="left" valign="top">&#x003C;.001</td></tr><tr><td align="left" valign="top"><italic>Salmonella</italic></td><td align="left" valign="top">35</td><td align="left" valign="top">3.3</td><td align="left" valign="top">22 (3.9)</td><td align="left" valign="top">13 (2.6)</td><td align="left" valign="top">1.5&#xFF08;1&#xFF09;</td><td align="left" valign="top">.22</td></tr><tr><td align="left" valign="top"><italic>Shigella</italic></td><td align="left" valign="top">0</td><td align="left" valign="top">0</td><td align="left" valign="top">0</td><td align="left" valign="top">0</td><td align="left" valign="top">0&#xFF08;1&#xFF09;</td><td align="left" valign="top">0</td></tr><tr><td align="left" valign="top"><italic>Vibrio parahaemolyticus</italic><sup><xref ref-type="table-fn" rid="table4fn1">a</xref></sup></td><td align="left" valign="top">31</td><td align="left" valign="top">2.9</td><td align="left" valign="top">24 (4.3)</td><td align="left" valign="top">7 (1.4)</td><td align="left" valign="top">7.8&#xFF08;1&#xFF09;</td><td align="left" valign="top">.005</td></tr><tr><td align="left" valign="top">Diarrheagenic <italic>Escherichia coli</italic></td><td align="left" valign="top">111</td><td align="left" valign="top">10.4</td><td align="left" valign="top">66 (11.8)</td><td align="left" valign="top">45 (9)</td><td align="left" valign="top">2.3&#xFF08;1&#xFF09;</td><td align="left" valign="top">.13</td></tr><tr><td align="left" valign="top"><italic>Norovirus</italic><sup><xref ref-type="table-fn" rid="table4fn1">a</xref></sup></td><td align="left" valign="top">60</td><td align="left" valign="top">5.6</td><td align="left" valign="top">43 (7.7)</td><td align="left" valign="top">17 (3.4)</td><td align="left" valign="top">9.2&#xFF08;1&#xFF09;</td><td align="left" valign="top">.002</td></tr></tbody></table><table-wrap-foot><fn id="table4fn1"><p><sup>a</sup>Indicates statistical significance (<italic>P</italic>&#x003C;.05).</p></fn></table-wrap-foot></table-wrap><p>Stacked bar charts show the number of positive cases for each of the 5 monitored pathogens in group A (2018&#x2010;2019) and group B (2022&#x2010;2023). <italic>Shigella</italic> had 0 positive cases in both periods. A notable decline in <italic>V parahaemolyticus</italic> positivity was observed in the postpandemic period. DEC remained the predominant pathogen in both periods (<xref ref-type="fig" rid="figure2">Figure 2</xref>).</p><fig position="float" id="figure2"><label>Figure 2.</label><caption><p>Bar chart of surveillance numbers and positive cases in 1064 foodborne disease cases.</p></caption><graphic alt-version="no" mimetype="image" position="float" xlink:type="simple" xlink:href="formative_v10i1e96940_fig02.png"/></fig><p>The chart illustrates the total number of patients tested (light blue) and the corresponding number of etiologically confirmed positive cases (dark blue) for each study year. The years 2020&#x2010;2021 were excluded due to major disruptions in clinical services and surveillance during the peak COVID-19 pandemic period. This exclusion represents an important limitation, as it precludes observation of pathogen trends during the period when infection control measures were most intense.</p></sec></sec><sec id="s4" sec-type="discussion"><title>Discussion</title><sec id="s4-1"><title>Principal Findings</title><p>This single-center retrospective study analyzed clinical and microbiological data from 1064 patients presenting to an infectious diarrhea clinic at a tertiary hospital in Beijing and compared microbial foodborne pathogen detection between the prepandemic (2018&#x2010;2019) and postpandemic (2022&#x2010;2023) periods. The principal finding was that the overall pathogen positivity rate among tested patients was significantly lower in the postpandemic period (82/503, 16.3%) compared with the prepandemic period (155/561, 27.6%), with <italic>V parahaemolyticus</italic> and <italic>Norovirus</italic> showing significant reductions. These findings are consistent with, but do not establish, a temporal association between the COVID-19 pandemic and changes in enteric pathogen detection.</p></sec><sec id="s4-2"><title>Interpretation of Findings and Comparison With Existing Literature</title><p>Among the 1064 cases, the predominant demographic comprised individuals aged 16 to 45 years (n=890, 83.6%), with students, civil servants, and retired personnel accounting for 762 (71.6%) cases. This pattern likely reflects the hospital&#x2019;s location, which is surrounded by academic and research institutions. In terms of clinical characteristics, the study population was predominantly aged 16 to 25 years, with students comprising the largest occupational group. Chen et al [<xref ref-type="bibr" rid="ref11">11</xref>] similarly reported that individuals testing positive were mainly young and middle-aged adults, highlighting the need for vigilance in monitoring students and other congregate populations.</p><p>The proportion of patients aged 26 to 45 and 46 to 65 years differed between group B and group A; however, because group B represents the postpandemic period (2022&#x2010;2023) rather than the strict lockdown period, this difference likely reflects a combination of factors, including altered health care&#x2013;seeking behavior, changes in the clinic&#x2019;s catchment population, differences in occupational composition, and other unmeasured variables rather than pandemic-related mobility restrictions.</p><p>In the etiological analysis, DEC remained the most frequently detected pathogen in both periods (group A: 66/561, 11.8%; group B: 45/503, 9%) [<xref ref-type="bibr" rid="ref12">12</xref>-<xref ref-type="bibr" rid="ref14">14</xref>], which is consistent with the findings of Liu et al in Haidian District [<xref ref-type="bibr" rid="ref15">15</xref>], who reported an 11.8% proportion of DEC. The persistently high detection of DEC may be related to its environmental resilience, low infectious dose, and potential for foodborne transmission through contaminated produce and other food vehicles. The relative stability of <italic>Salmonella</italic> detection rates between periods (group A: 22/561, 3.9%; group B: 13/503, 2.6%) is consistent with its endemic circulation in animal reservoirs and continuous food supply chain contamination, which may be less affected by personal hygiene measures [<xref ref-type="bibr" rid="ref16">16</xref>,<xref ref-type="bibr" rid="ref17">17</xref>].</p><p>The significant reduction in <italic>V parahaemolyticus</italic> detection, from 24/561 (4.3%) to 7/503 (1.4%), is noteworthy [<xref ref-type="bibr" rid="ref18">18</xref>,<xref ref-type="bibr" rid="ref19">19</xref>]. This pathogen is classically associated with seafood consumption, particularly raw or undercooked shellfish. The observed decline may reflect changes in food consumption patterns during and after the pandemic, including reduced restaurant dining, increased home cooking, and possible disruptions in seafood supply chains. Additionally, <italic>V parahaemolyticus</italic> has a summer seasonal peak, and changes in health care&#x2013;seeking behavior for mild diarrhea during summer months may have contributed to the observed reduction. <italic>Norovirus</italic> detection also declined significantly, from 43/561 (7.7%) to 17/503 (3.4%) (<italic>P</italic>=.002), which is biologically plausible given that <italic>Norovirus</italic> can be transmitted through the fecal-oral route and aerosols; thus, enhanced hand hygiene, mask wearing, and environmental disinfection measures implemented during the pandemic may have reduced its transmission [<xref ref-type="bibr" rid="ref20">20</xref>,<xref ref-type="bibr" rid="ref21">21</xref>].</p><p>No <italic>Shigella</italic> cases were identified in either group, which is consistent with the findings of Wang et al [<xref ref-type="bibr" rid="ref22">22</xref>], who reported a gradual decline in <italic>Shigella</italic> among foodborne pathogens, and with Lu et al [<xref ref-type="bibr" rid="ref23">23</xref>], who noted high <italic>Norovirus</italic> detection rates among viral pathogens and high DEC detection rates among bacterial pathogens. Among cases of foodborne illness, the relative proportions of <italic>Salmonella</italic> and DEC were higher in group B than in group A, suggesting that these pathogens may require continued surveillance.</p></sec><sec id="s4-3"><title>Alternative Explanations and Limitations</title><p>It is critical to distinguish between a reduction in detected cases and a true reduction in population-level disease incidence. This hospital-based study cannot establish population-level incidence. The observed lower positivity rate may reflect multiple factors beyond a true decline in disease occurrence, including (1) changes in health care&#x2013;seeking behavior, whereby patients with milder symptoms may have been less likely to visit the hospital during and after the pandemic; (2) altered health care accessibility and clinic volume; (3) changes in food consumption patterns, including increased home food preparation and reduced dining out; (4) changes in stool sampling practices and clinician testing thresholds; and (5) nonpharmaceutical interventions (hand hygiene, masking, social distancing) that may have genuinely reduced the transmission of enteric pathogens. We are unable to disentangle the relative contributions of these factors in this observational study.</p><p>Several additional limitations should be acknowledged. First, this was a single-center study conducted at one infectious diarrhea clinic in a tertiary hospital in Beijing; therefore, the findings may not be representative of the general population or community-level epidemiology in China or in other geographic regions. This study included only symptomatic patients seeking care, which likely excluded milder cases and asymptomatic infections. Second, the exclusion of the 2020&#x2010;2021 time period represents a major gap, as this period encompassed the peak of the pandemic, when infection control measures were most intense. This created a discontinuity in temporal trends and meant that we could not characterize changes during this period. Third, we investigated only 5 bacterial and viral pathogens; nonmicrobial foodborne illnesses (chemical contamination, natural toxins, food allergies, and parasites) were not assessed, and thus our results do not represent the full spectrum of foodborne diseases. Fourth, statistical analyses were limited to univariate comparisons, and we were unable to perform multivariate adjustment for all potential confounders. Fifth, the sample size for some individual pathogens was small, limiting statistical power for subgroup comparisons. Finally, we did not have data on total clinic visit volumes to directly quantify changes in health care utilization.</p></sec><sec id="s4-4"><title>Implications</title><p>In clinical practice, early management of suspected foodborne cases, particularly those involving DEC and <italic>Salmonella</italic>, should include appropriate infection control measures, such as hand hygiene, use of masks and gowns, patient education on personal hygiene, environmental disinfection, vital sign monitoring, and dietary guidance. For severe cases, temporary fasting and nutritional support may be required [<xref ref-type="bibr" rid="ref24">24</xref>,<xref ref-type="bibr" rid="ref25">25</xref>]. Future efforts should strengthen foodborne disease surveillance through diversified health education channels and coordinated online and offline public awareness campaigns to improve food safety knowledge.</p></sec><sec id="s4-5"><title>Conclusions</title><p>Among patients presenting to a single infectious diarrhea clinic in Beijing, detection rates of bacterial and viral foodborne pathogens were significantly lower in the postpandemic period (2022&#x2010;2023) compared with the prepandemic period (2018&#x2010;2019), with <italic>V parahaemolyticus</italic> and <italic>Norovirus</italic> showing significant declines. These temporal changes may be associated with infection control measures, shifts in health care&#x2013;seeking behavior, and changes in food consumption patterns; however, this observational study cannot establish causation, and the results do not represent population-level incidence or the full spectrum of foodborne diseases. Continued surveillance and further multicenter studies incorporating longer study periods and molecular subtyping are needed to better understand the long-term implications of the pandemic for foodborne disease epidemiology.</p></sec></sec></body><back><ack><p>The authors attest that no generative AI tools were used in the preparation of this manuscript.</p></ack><notes><sec><title>Funding</title><p>The authors declared that no financial support was received for this work.</p></sec><sec><title>Data Availability</title><p>The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.</p></sec></notes><fn-group><fn fn-type="con"><p>Conceptualization: LT</p><p>Data curation: LT</p><p>Formal analysis: CL</p><p>Investigation: LT</p><p>Methodology: CL</p><p>Project administration: CL</p><p>Supervision: CL</p><p>Validation: HZ</p><p>Visualization: HZ</p><p>Writing - original draft: LT</p><p>Writing - review &#x0026; editing: 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